Modeling Apples And Oranges

During a climate change discussion[1] on Inside Washington, conservative commentator Charles Krauthammer acknowledged that "we're pumping more CO2 into the air than ever before, much higher than a natural rate and it's having an effect on the atmosphere." Krauthammer, who calls himself[2] "a global warming agnostic," went on to dismiss the computer models scientists use to project future climate change:

KRAUTHAMMER: Our models are extremely incomplete, as we see in weather predicting. We can predict up to about a week and after that, it's a mess. So predicting, 20, 30, 50, 100 years into the future -- and our predictions are constantly changing, which ought to tell you that the models are at least incomplete and deficient.

I'm glad that Krauthammer, unlike so many of his[3]colleagues[4]at[5]Fox[6]News[7], acknowledges that humans are changing the climate. But his argument about climate modeling is wrong.

For one, models of any sort are by definition "incomplete." Scientists use models because we don't have a second Earth to experiment on. The question is, do the models know enough about the climate system to provide a useful picture of how it might look under a given scenario?

Climate experts say yes, but Krauthammer seems to disagree, noting that weather forecasts aren't reliable beyond a week into the future. It's a common argument: If we can't predict next month's weather, how can we say anything about the climate in 2100? In reality, invoking the limitations of weather predictions is a terrible way to evaluate climate models.

While weather forecasters seek to predict in detail the conditions at a specific time and place, climatologists project slow-changing average conditions over a longer time period and a larger area. Explaining this distinction, the Intergovernmental Panel on Climate Change offers[8] a coin toss analogy:

[L]ong-term variations brought about by changes in the composition of the atmosphere are much more predictable than individual weather events. As an example, while we cannot predict the outcome of a single coin toss or roll of the dice, we can predict the statistical behaviour of a large number of such trials.

To forecast tomorrow's weather, the most important thing you need to know is today's weather. As the scientists at RealClimate.org explain[9], "Weather models use as much data as there is available to start off close to the current weather situation and then use their knowledge of physics to step forward in time." Small discrepancies in these initial conditions will lead to major problems in the forecast and the errors get worse as you run the model farther into the future.

But the atmosphere's inherently chaotic day-to-day variations, which make weather forecasts beyond a week problematic, don't trip up the climate models. "Weather is dominated by your starting conditions," John Abraham of the University of St. Thomas said via email, and "climate is dominated by external forces like the sun, greenhouse gases, amount of ice, and so forth." Climatologists create a virtual climate system that can simulate not only current conditions but also previous points in Earth's history when climatic conditions differed greatly from today's, such as the last ice age.

In a recent report[10] reviewing the state of climate knowledge, the National Research Council said scientists are "confident that climate models are able to capture many important aspects of the climate system":

After decades of development by research teams in the United States and around the world, and careful testing against observations of climate over the past century and further into the past, scientists are confident that climate models are able to capture many important aspects of the climate system. Scientists are also confident that climate models give a reasonable projection of future changes in climate that can be expected based on a particular scenario of future GHG emissions, at least at large (continental to global) scales.

Indeed climate models have been evolving for over 50 years[11] and continually advance[12] as observations, computing and knowledge improve. Scientists' confidence in these models, which still face important limitations[13], "comes from the foundation of the models in accepted physical principles and from their ability to reproduce observed features of current climate and past climate changes," according to the IPCC's 2007 discussion[14] of climate models and their evaluation.

No one should expect climate modelers to produce a crystal ball. But as a critical segment[15] of climate science, today's models are sophisticated and endure perpetual scrutiny. When the best available science warns of significant climate changes, dismissing these models is not a cautious or thoughtful response.